Learning Aloud

Damage from time online?

The benefits and harms done by our devices and the ways we use them is one of those topics likely of at least marginal interest to most people. We wonder whether we have become too dependent and whether existing interests and capabilities have deteriorated. If we are a parent or educator we likely have additional unique interests. Have I messed up my kid by letting him or her use a phone without supervision? How do I keep my students on track in the classroom and are they using AI to complete my assignments quickly without any actual educational benefits?

My personal interest goes a bit further in that I spent my career preparing educators to use technology in their classrooms and I by training feel responsible for understanding the science behind recommendations made to others. So, I review the research on many topics. From this perspective, I would offer the following observation – it is seldom as simple as it seems. I know this to be true in the social sciences which would be the field covering phone use and the impact on development and learning. This is the case for many reasons and far from a topic I can thoroughly consider here. One comment I used to make to my own students may be helpful. For context, I was trained as a biologist who became a psychologist. My comment was – students tend to see a discipline like chemistry as more sophisticated and complicated than psychology. Consider that the chemicals in that beaker don’t decide whether they feel like reacting today. People are different.

Back to the issue of our devices and the research on how we are being impacted. I recently read a book by Jonathan Haidt titled The Anxious Generation. Many people must have read this book because it topped the New York Times best-seller list for several weeks which I interpret to mean many parents and educators are concerned and were attracted by the topic. Recommendations made in the book, for example, no phones in schools, have been implemented in many schools. I read Haidt’s book in response to such changes concerned my pro-technology advocacy should be tempered. I admit my initial reaction was that Haidt made a reasoned and evidence-based case. However, I have learned that such secondary sources need to be vetted and I was concerned by some of Haidt’s rationale which I would describe as “what else besides iPhones and Instagram” could explain the mental health issues of adolescent females. The “what else could it be” logic just seems weak. In reaction, I read a related, but less well-known book by Pete Etchells and as I suspected the issue is complicated.

What follows is my summary of the two books with some related comments.

Comparing Perspectives on Screen Time and Mental Health

Haidt’s “The Anxious Generation”

In “The Anxious Generation,” Jonathan Haidt really covers two broad problems he contends have changed the mental health development of children and adolescents. Children have been overprotected in their daily lives resulting in a lack of play and autonomy involving risks and consequences. In contrast, the author argues that the rise of smartphones and social media have been largely unmonitored and unrestricted with negative consequences to mental health. I will comment on both claims, but emphasize technology use.

Haidt highlights the following key points:

Slow-Growth Childhood: Human children have an extended childhood compared to other mammals, providing them with time to learn through play and social interactions. This extended childhood is crucial for emotional and cognitive development.

Importance of Play: Play-based childhoods are essential for healthy development, fostering skills such as emotional regulation, social competence, and creativity.

Safetyism: Haidt argues that the overprotective parenting style prevalent in the 1990s, termed “safetyism,” limited children’s opportunities for risk-taking and independence, further contributing to anxiety. Haidt uses example older folks will find familiar – e.g., playground equipment that is no longer allowed for safety reasons and reduced independence in moving about the neighborhood or in solo trips to the store.

Negative Impacts of Smartphones: These problems include:

Social deprivation: Replacing face-to-face interaction with screen time.

Sleep deprivation: Late-night phone use cutting into sleep at ages when necessary. The early school start for adolescents is an example of when this becomes a problem.

Attention fragmentation: Constant notifications and multitasking impairing focus.

Addiction: The design of social media platforms promoting addictive behaviors. Etchells will reject this notion if understood as a physiological addition as in drug use.

Puberty as a Sensitive Period: Puberty is a critical period for brain development, making adolescents particularly vulnerable to the negative effects of social media. Hence, experiences allowed at other ages may do less damage.

What evidence suggests that puberty is a “sensitive period” for social media use?

Brain Development: Puberty to a greater degree than the earlier period of childhood involves the pruning of neurons and the strengthening of connections, processes influenced by experiences. This heightened neuroplasticity implies that experiences during puberty, including social media use, can have a greater and more enduring impact on brain structure and function.

Orben’s Research: Amy Orben, found that negative correlations between social media use and life satisfaction were more pronounced in the 10-15 age group, encompassing puberty, compared to older individuals (16-21). This finding directly supports the idea of puberty as a sensitive period for social media’s influence on well-being.

Social Learning and Conformity: Adolescents are conformers, a process that social media platforms can strongly influence. Puberty marks a time when individuals are particularly sensitive to social cues and peer influence, seeking to establish their identity and social standing. Social media platforms, with their emphasis on likes, followers, and influencers, can hijack this natural drive for social learning, potentially leading to distorted perceptions and unhealthy comparisons. Giirls are most vulnerable to social media’s negative effects between 11 and 13, while boys experience this heightened vulnerability between 14 and 15. This timeframe aligns with typical puberty onset, further suggesting that the hormonal and social changes during this period make adolescents more susceptible to the pressures and comparisons prevalent on social media.

In conclusion, the sources provide converging evidence pointing to puberty as a “sensitive period” for social media use. This sensitivity stems from the interplay of rapid brain development, heightened social awareness, and the drive for conformity, all characteristic of adolescent development. This information suggests that social media use during puberty requires particular attention and potentially different approaches compared to other age groups.

Haidt makes use of historical data linking changes in mental health data over the years to changes in the technology available to young people. Much of Haidt’s argument about the damage done by access to the Internet is made by tracking mental health outcomes against dates associated with changes in technology. Gen Z started to reach puberty in 2009. iPhones became available in 2009. Social media capabilities such as retweets and likes became available in 2009. Front facing cameras in 2010. Facebook acquired Instagram in 2012. His challenge to critics is what else could have accounted for the changes in adolescent mental health that correspond to this time frame.

Recommendations: Haidt proposes four solutions to address this issue: no smartphones before high school, no social media before age 16, phone-free schools, and promoting more unsupervised play and childhood independence.

Etchells’ “Unlocked”

Pete Etchells, in his book “Unlocked: The Real Science of Screen Time (and how to spend it better)” offers a more nuanced view of screen time and its relationship to mental health.

Etchells first notes that the consequences of technology and social media likely include both positive and negative impacts so explanatory models must take into account both possible outcomes. Etchells’ key arguments include:

Screen Time is Complex: Etchells argues simply measuring the total amount of screen time is insufficient to understand its impact on well-being. What matters is how screen time is used, the specific apps and content consumed, and the context of use.

Limited Evidence for Strong Negative Effects: While some studies have shown correlations between screen time and mental health issues, the evidence is mixed, with many studies showing small or inconsistent effects. The existence of correlations even if the correlation reflected a causal relationship with negative changes in mental health as a consequence do not necessarily show large effects. The impact is typically small.

Etchells critiques the reliance on anecdotal evidence and highlights methodological limitations in much of the research. One of the most important methodological limitations appears to be whether self-reports versus verifiable behavioral data are used. Even though digital devices are great at recording data on use (consider your iPhone and your daily report of time spent on different apps) many studies ask users to estimate their time spent and activities experienced. When studies using self-report data are compared with studies using the more accurate data collected by the devices used, significant relationships are typically found only with the self-report data. Etchells speculates that user awareness of screen time issues and potential negative consequences results in participants in these studies interpreting negative personal experiences as an indication of too much screen time. How individuals feel about their screen use and their perceived self-control are more strongly related to well-being than objective measures of screen time.

Importance of Habits over Addiction: Etchells argues that framing excessive screen use as “addiction” is unhelpful, as it focuses on abstinence as the only solution. Instead, he advocates for viewing screen use as a set of habits that can be modified to promote well-being. The author argues that the assumption of a physiological explanation (probably dopamine) within the framework of addictions such as drug abuse is what readers of many of the negative books assume. Addiction tends to ignore agency and motivation. This is where the notion of habits also fits and solutions that are more nuanced with a focus on decision-making and awareness.

Oversimplification of “Screen Time”: Etchells argues that simply measuring the total amount of time spent in front of screens is too crude a metric to be meaningful. He emphasizes that “screen time” encompasses a vast range of activities, from educational apps to social media to video games, each with potentially different effects on well-being. He contends that focusing solely on duration ignores the crucial factors of content, context, and purpose of use.

Reliance on Anecdotal Evidence: Etchells criticizes the prevalent use of anecdotal stories to support claims about the negative impacts of screen time. While these stories can be compelling and relatable, he argues they often lack scientific rigor and can lead to biased conclusions. We like stories because we often can relate to such examples and do not necessarily make the same connections with the data in graphs and statistics. Of course, coming up with examples that fit a perspective does not necessarily fit what is most common in a sample of participants. He points out that reliance on anecdotes is particularly problematic in a relatively new field like digital technology research, where robust, longitudinal data is still limited.

Methodological Issues in Correlational Studies: Much of the research on screen time relies on correlational studies, which can only demonstrate associations, not causal relationships. Etchells highlights the problem of “third variables,” unaccounted-for factors that might influence both screen time and mental health, leading to spurious correlations. For example, pre-existing mental health conditions, family dynamics, or socioeconomic factors could contribute to both increased screen time and negative well-being outcomes, creating the illusion of a direct link where none exists. Correlations showing relationships do not necessarily convey the magnitude of an effect. A significant correlation in a large population may be associated with a very small impact.

Lack of Theoretical Framework: Etchells argues that the field lacks a robust theoretical framework to guide research and interpret findings. He suggests that without clear theoretical models, researchers are left to “grasp at straws,” making tenuous connections between screen time and a wide range of outcomes without a solid foundation for understanding the underlying mechanisms. This lack of theoretical grounding makes it difficult to develop testable hypotheses and draw meaningful conclusions. Haidt’s “what else could it be” argument fits here.

Ambiguous Terminology: Etchells points out the imprecise use of terms like “addiction” and “attention” in screen time research. He criticizes the tendency to label excessive screen use as “addiction” without sufficient evidence of a true physiological dependence. He also argues that “attention” is often used interchangeably with “self-control,” leading to conceptual confusion and misinterpretations of research findings.

Insufficient Attention to Positive Effects: Etchells argues that the focus on potential negative consequences of screen time has overshadowed research on its potential benefits. He acknowledges that excessive or problematic screen use can be detrimental, but he emphasizes the importance of recognizing the many ways in which technology can enhance learning, communication, and social connection. He encourages a more balanced approach that considers both the positive and negative aspects of screen time.

In conclusion, Etchells urges caution against drawing sweeping conclusions about the impact of screen time based on the existing research. He advocates for more nuanced investigations that consider the complexities of technology use, adopt rigorous methodologies, and develop strong theoretical frameworks to guide future research.

Comparing Haidt and Etchells

While both Haidt and Etchells acknowledge the potential downsides of excessive screen time, they differ significantly in their overall perspectives and conclusions:

Emphasis on Negative Effects: Haidt emphasizes the negative impacts of smartphones and social media, attributing a rise in mental health problems directly to these technologies. Etchells, on the other hand, acknowledges the potential for harm but argues that the evidence for strong negative effects is weak and often overstated.

Role of Social Media: Haidt sees social media as a particularly harmful force, promoting conformity, comparison, and addiction. Etchells recognizes these potential issues but maintains that social media can also have positive benefits, depending on how it is used. The existence of both positive and negative outcomes argues against simplistic abstinence/avoidance and urges more careful personal awareness and control.

Solutions: Haidt proposes strict limitations on smartphone access and social media use, advocating for a return to a more play-based childhood with less adult supervision. Etchells focuses on promoting healthy screen habits, emphasizing individual agency and self-regulation rather than strict restrictions.

Conclusion

Haidt’s “The Anxious Generation” presents a compelling, albeit alarming, argument about the potential downsides of technology for young people. However, Etchells’ “Unlocked” offers a more balanced perspective, urging caution against oversimplifying the complex relationship between screen time and mental health. The key takeaway is that understanding the nuances of screen use and focusing on developing healthy habits is crucial for mitigating potential harms and maximizing the benefits of technology. Both books highlight the importance of critical thinking and evidence-based approaches when evaluating the impact of technology on our lives.

Sources:

Etchells, P. (2024). Unlocked: the real science of screen time (and how to spend it better). Hachette UK

Haidt, J. (2024). The anxious generation: How the great rewiring of childhood is causing an epidemic of mental illness. Random House.

Hooked on Online Writing

I have been reading Robert Haidt’s “The Anxious Generation”. This post is not a description of that book, but the book’s focus and content were the origin of my present topic. The book, which has topped the New York Times best-seller list for some weeks, focuses on the mental health damage of the way kids are raised in combination with the negative impact of social media. Haidt is particularly concerned about young girls and their susceptibility to the negative consequences of what becomes a damaging addiction to social media. While male and 75, I had an uneasy feeling Haidt could have been describing me and my preoccupation with a different online environment. Before I get to my personal insight, allow me to describe the characteristics Haidt argues drive the general problem that is the focus of his book.

Haidt proposes that the writings of B.J. Fogg have served as the bible guiding many social media entrepreneurs. I usually read the core literature associated with what I write, but Fogg’s book was priced at textbook levels and I decided I was very familiar with the central content (a different source). Fogg successful persuasion can be accomplished based on behavioral principles any college student who has taken the Introduction to Psychology course will recognize. His terminology is a little different. When I taught the Intro course, I described the process Fogg and Haidt emphasize as operant conditioning. A very simple version of the way operant conditioning changes behavior is captured in the sequence – stimulus – response – consequences. Behavior changes (response) are encouraged by positive consequences. When used to account for what seems an addiction to online social media in children, the response might be frequent checking of a social media account and the positive reinforcers (likes, comments, attention, etc.). Access to a phone (the stimulus) triggers the initial behavior generating the consequences.

The Fogg version is described in the following model.

Fogg uses a little different vocabulary. The external trigger is his term for stimulus and action is the behavior. Variable reinforcement is another concept from behavioral psychology that translates as a situation in which a behavior does not produce a consequence every time it is produced. This unpredictability increases the frequency of behavior. A common example is the way a slot machine works. A gambler would soon quit if previous experiences were always wins and now the machine stops paying out. You tend quit putting coins into a vending machine if the first attempt or maybe the second produces no soda or candy bar. If however, a slot machine generates wins now and then people keep feeding their coins.

Fogg and Haidt add one additional component to the model – investment. Social media often has another characteristic increasing holding power. The example of investments are everywhere online. Do you play that online game where you have to guess the spelling of a mystery word within so many tries? If you have a streak of days going, you have an investment that makes it very likely you will not miss a day. Do you take photos or use AI to create photos to embellish your posts? You are making an investment. Do you pay to add weapons or clothing (skins) in an online game? You are investing. When your identity becomes part of your participation in an activity, you are heavily invested. I would suggest making political comments on social media are a good example of being invested. Our political affiliations are part of our identities. Haidt argues that Instagram has such a powerful impact on young females (often negative) because the photo-heavy nature of the platforms triggers the role appearance has in the identity of young women.

Social media involves a switch from external triggers to internal triggers. Once you are involved, you don’t have to be sent a message that you have a new like or comment. You don’t have to see your phone sitting on your desk. Your thoughts lead you to get your phone out of your pocket or purse to check your accounts to see if anything new has shown up.

Haidt emphasizes the powerful impact of social media on the attention and mental health in children and adolescents. I saw a similarity in the application of the model and the arguments made to adults who write on blogs, Substack and Medium. I don’t think the negative impact holds in the same way because of the life experiences and brain maturity (frontal cortex and metacognition) of adults and draw the following parallels more out of amusement than concern. If there was one insight that triggered me to write this post, it was the recognition of identity in motivating behavior more so than the behavioral explanation. For those who write, writing for public consumption is part of personal identity. I think the behavioral impact on behavior is more powerful because of this self view.

Here is my attempt to apply the cycle of engagement (Haidt and Fogg) to writing:

1. Trigger

The cycle starts with a trigger that prompts users to take an action. Triggers can be:

External triggers: Notifications, emails, messages, ads, or reminders that tell users to open an app or take action. For example, a push notification letting you know someone liked your post.
Internal triggers: Emotions, thoughts, or desires that come from within, like boredom, curiosity, just wondering if there is something there. These feelings push users to check their phone or social media without an external prompt.

2. Action

After the trigger, the user performs an action. The action may be simple such as seeing if anyone has read your post or liked your content. There may be statistics or charts to check. The actions that are triggered can be more involved such as researching and writing another post.

3. Variable Reward

Once the action is taken, the user receives a reward, but to keep engagement high, the reward is often variable or unpredictable. This uncertainty makes the reward more powerful or resistant to extinction in behavioral terms.

Social rewards: Users may get more or fewer likes, comments, or shares on their posts each time, keeping them hooked. In some writing platforms, there is financial compensation to check.

4. Investment

The final stage of the cycle is investment, where the user puts something of value back into the platform. This investment can be time, effort, data, or emotional input, and it increases the likelihood that the user will return to the platform. Examples include:

Creating content: Posting a photo, video, or comment.
Personalization: Customizing a profile or favoriting the work of others.
Building relationships: Adding friends, replying to messages, or participating in communities.This investment helps users feel more connected to the platform because they’ve contributed, and it primes them for future triggers. As they invest more, they become more likely to engage again, as their investment increases the value of the platform to them
Financial commitment: Payment of a fee to participate.
Affirmation of identity: The content I generate and share demonstrates I am a writer.

5. Repeat

Once users have invested in the platform, they receive new triggers, starting the cycle all over again. Over time, this cycle builds a habit, with users increasingly relying on internal triggers, such as boredom or curiosity, to engage with the platform.

If you are a writer who contributes content online, you may see yourself in this description. With social media, such models are used to describe how participants are drawn into spending more and more time in such environments sometimes with negative emotional consequences. I will leave it to your own analysis to determine whether being drawn into a platform to which you contribute your writing impacts your emotional well-being.

Reference

Fogg, B.J. (2003). Persuasive technology: Using computers to change what we think and do (Interactive Technologies).

Upload Obsidian Folders to NotebookLM

Many of us have now had the opportunity to spend considerable time with AI tools and have sorted out for ourselves what types of applications are most productive. For my personal use, I found the greatest value in the use of AI to analyze the notes and highlights I have accumulated over the years to search for insights I might use in my writing projects. I keep most of my notes in Obsidian and one of the more popular posts I have generated focusing on AI and personal notes explained my approach to using the Obsidian AI extension Smart Connections.

As I continue exploring, I have found another approach that others may find useful. This approach uses the Google AI tool NotebookLM. This tool is presently provided at no cost and is easy to use. There is a frustrating mismatch between how most of us use Obsidian and the structure of NotebookLM. Obsidian users typically create many short notes and then create links and tags to allow these notes to be stored and used in the most flexible manner possible. NotebookLM allows the uploading of considerable content into an individual notebook to be explored with AI chats, but limits the number of files that can be included. This combination – many small files in Obsidian and a limited number of files in NotebookLM notebooks – creates a challenge.

Here is my present solution. There is an extension for Obsidian (Better Export PDF) that allows the content from multiple files stored within an Obsidian folder to be exported as a single PDF. You can probably see where this is going. Export the many files in several folders as PDFs and then add these PDFs to NotebookLM.

The Better Export PDF in Obsidian

The following image was captured as I used Obsidian. You can see the multiple folders I have created. After One Better Export has been added to Obsidian, you first right-click (control click) on a folder to bring up various options. The one you want is Export folder to PDF.

Activating this option may leave you confused as the process takes some time to accomplish. You know when things are working properly when you see the names of individual files appear towards the top of the display (red box). When the process of concatenating the files has been completed the complete PDF file will appear in what initially appears as white space. Now you export this large file.

You complete this process additional Obisian folders until you have exported the large PDFs you want to explore in NoteBookLM.

NotebookLM AI Chat

The following image shows a notebook I have created based on three PDFs (Cognitive, Generative, Notetaking). A couple of hundred individual notes are included in these three large files. At the bottom of the image, you should find a prompt I have entered.

For AI tool users, everything should now be more familiar. NotebookLM has responded to my original prompt and I can accept some of the recommendations for related topics I might explore (not shown). NotebookLM offers a way to review the content the AI used to generate the prompt reply (numbers in the red box). Selecting one of these numbers takes you to the section in your input and allows you to explore that context.

Summary

So, this combination of Obsidian and NoteBookLM seems to work well. The key is the Obsidian extension Better Export PDF which allows many Obsidian notes to be combined to address the limited number of files NoteBookLM will accept as input. Give it a try.

Reading and what we know

In reading and then writing about Willingham’s The Reading Mind, the author makes some interesting arguments about the relationships between what we know and reading comprehension and between the time spent reading and what we know. As the reciprocal relationship implies, this is a cognitive explanation of how the rich get richer. The author throws in a related analysis of whether our commitment to spending time with technology has diminished the likelihood that we are now benefiting from this relationship. What follows is my embellished summary with a few updates.

I like to think of Willingham’s description of reading as explaining how the inputs to comprehension come simultaneously from opposite directions. The bottom-up inputs come from the page – letter/phoneme recognition, word recognition, word meaning, broader understanding. The top-down inputs come from stored information (memory) – general knowledge, specific knowledge, broad understanding of the passage being read, sentence meaning, etc. You probably recognize that these inputs are really the same series just listed in opposite directions. It turns out these inputs help each other out as many are being processed at the same time. Some of these interactions you may not recognize and may surprise you. For example, a letter at the beginning of a word can be identified faster than the letter in isolation. Others, you may recognize if I bring them to your attention. For example, the understanding of a sentence may help you assign meaning to an unfamiliar word in that sentence. The battle over what is commonly described as the “science of reading” is focused on the early bottom-up processes. Should early reading experiences emphasize associating sounds with word components or should word recognition and context receive greater attention? It might be helpful to understand why the science of reading may seem to change over time because effective reading depends on multiple processes acting to support each other. Many subskills end up being important. I am more interested here in the top-down processes. Once we get past learning the basics of reading, how does reading both depend on and develop what we know?

Willingham proposes that it is never possible for a writer to explain a topic in complete detail and an author must rely on what readers already know to fill in some elements from existing knowledge. So when a reader is exposed to new material understanding is dependent both on reading skill and existing knowledge. What we already know has a surprisingly large impact on what we comprehend and retain. This claim can be demonstrated on two levels – general knowledge and topic specific knowledge.

Anne Cunningham and Keith Stanovich conducted an interesting study of high school students in which they had the students take a test of general knowledge. General knowledge involves all kinds of random information. In their research, students were asked about factual knowledge of science, history, and literature and the accomplishments of people from history, science, sports, and music. It was not that the knowledge of the specific topics was necessarily important, but rather that the scores obtained were predictive of the level of general knowledge more broadly. The researchers also administered a standard test used to evaluate reading comprehension skills. These two variables – general knowledge and comprehension skill were strongly correlated. More capable readers probably have learned more from reading, but what they have learned may also be a factor in determining their reading skill. Such differences are partly responsible for the advantage some students gain from general life experiences that cannot be provided while in the classroom.

The advantage of what we know to reading performance is made clear in studies that investigate the importance of specific knowledge in understanding content related to that knowledge. Willingham used a study based on reader differences in understanding the game of soccer. This surprised me as I was aware of a very similar study based on the game of baseball. A general description of the clever methodologies of these studies will explain how reading skills and relevant knowledge were differentiated. These studies (Recht & Leslie, 1988; Schneider, Korkel & Weinert, 1989) were conducted with younger learners. Depending on the study, these learners were given a test to evaluate their knowledge of baseball or soccer. Scores on reading comprehension tests were also available. These two measures were used to identify four groups of learners – high on both measures, high on one measure and low on the other, low on both measures. After reading a story about part of a baseball game or a soccer match, readers were asked to recall as much as they could from the story. The grouping of readers allowed a way to statistically isolate the impact of reading ability from background knowledge on what was retained. Relevant knowledge was at least as important as reading proficiency to what was taken away from the reading experience. By the way, this type of research should be relevant to those who argue access to Google is equivalent to knowing things. What you can find through search does not offer the same benefit to immediate processing as what you already know.

Leisure Reading and Technology

Leisure reading plays a unique role to developing readers because the time devoted to leisure reading varies far more than the time spent reading in schools. As adults, if we read many of us only engage in reading that would fall in this category. If engaged in an educational setting, leisure reading augments assigned reading as a reading skill development opportunity and as an opportunity to expand the acquisition of general knowledge and that is important in improving the effectiveness of reading.

In the discussion of technology and reading, Willingham considers both whether reading from a screen offers the same benefits as reading from paper and whether our constant use of technology has displaced time spent reading. Willingham acknowledges the research that demonstrates a small benefit for reading from paper. Like my posts on this topic, he sees this difference to be of little consequence acknowledging that the root cause is unknown. My embrace of screen reading is related to the long-term advantages of the production of digital notes and searchable highlights that can be organized and efficiently searched.

The notion that screen time comes at the cost of reading time (displacement) was countered with what to me were some surprising data. In his focus on leisure reading, Willingham argues that Americans never did read much and that this amount of time has not diminished from pre-internet days. I checked Willingham’s sources on this topic and found a more recent survey of adolescent reading behavior (Rideout and colleagues 2022). Reading time has actually increased a bit, but the average daily reading time has now reached 34 minutes. Twenty-four minutes involve books (paper or ebooks) and the rest newspapers, blogs, and other long-form content. I don’t find this average that disturbing given students are also reading for their classes and may have homework. The more disturbing version of this basic statistic is the variability. Nearly 20% of adolescents indicate they read nothing beyond what is assigned at school. Recent data on adult behavior indicates that the average daily reading time is about 15 minutes. Adults don’t set a very good example.

Summary

Reading both is an important source for what we know and what we know benefits the level of reading proficiency we achieve. Reading is an activity we control as individuals and if we so choose we can benefit from spending leisure time in this way.

References:

Cunningham, A. E., & Stanovich, K. E. (1997). Early reading acquisition and its relation to reading experience and ability 10 years later. Developmental psychology, 33(6), 934.

Recht, D. R., & Leslie, L. (1988). Effect of prior knowledge on good and poor readers’ memory of text. Journal of Educational Psychology, 80(1), 16–20. https://doi.org/10.1037/0022-0663.80.1.16 (baseball)

Rideout, V., Peebles, A., Mann, S., & Robb, M. B. (2022). Common Sense Census: Media use by tweens and teens, 2021. San Francisco, CA: Common Sense Media

Schneider, W., Korkel, J., & Weinert, F. E. (1989). Domain?specific knowledge and memory performance: A comparison of high? and low? aptitude Children. Journal of Educational Psychology, 81( 3), 306–312. (Soccer)

Willingham, D. T. (2017). The reading mind: A cognitive approach to understanding how the mind reads. John Wiley & Sons.

The Science of Reading: A Review of Three Recent Books

I read a lot, but aside from posting short reactions to Goodreads I seldom write longer reviews. I was able to get the book club I attend that typically focuses on history, economics, and writing to read my suggestion – Adrian Jones’ The Science of Reading. Despite the departure from our standard fare, the breadth of the issues covered using reading and learning to read as a base resulted in many engaging discussions. The present political interest of some states in mandating how children should be taught to read, the history of the “reading wars”, the big money up for grabs in school purchases of instructional materials (books), how digital technology changed reading, and why this particular skill is so important have encouraged broader interest in how best to prepare readers and in how we all engage with text. There is something for nearly everyone here.

The three books I will comment on cover these topics with different emphases. The Science of Reading (Jones) offers the strongest historical perspective. Reader, Come Home (Maryann Wolf) emphasizes a brain-based perspective. Willingham’s The Reading Mind approaches the set of topics from a cognitive perspective. All are approachable and as an educational psychologist with a cognitive background, I see value in how different perspectives support and supplement each other.

Adrian Johns’s “The Science of Reading: Information, Media & Mind in Modern America”

Johns covers the scientific study of reading from the 1880s to the present and argues that understanding the history of the science of reading is essential to understanding broader historical changes in knowledge, information, and technology. He achieves this by tracing the evolution of how reading has been perceived and taught, particularly in the United States, where reading has been closely linked to concerns about effective participation in a democracy. The assumed connection between reading and the economy and reading and informed citizenship are reflected in the long-term interest of politicians in this subject area.

The book begins by examining the origins of the science of reading, which can be traced back to the late 19th century, and the interest of scientists in the movement of the eyes (saccades) while reading. Early researchers like James McKeen Cattell (a name many might recognize from an Introduction to Psychology class) focused on the psychophysical aspects of reading, conducting experiments to measure reaction times and investigate how the human eye processes visual information. Cattell’s research led him to advocate for teaching reading through whole-word identification, a method that gained traction in American schools. For those involved in or recognizing the battle over how best to teach reading, the alternative extremes are to emphasize word recognition or sounding out words by what most would describe as phonics.

However, as Johns illustrates, the science of reading was not solely driven by laboratory findings. An emphasis on mass literacy further fueled the development and adoption of different reading methods, reflecting the intertwined nature of scientific inquiry and societal needs.

Edmund Burke Huey’s influential 1908 book, “The Psychology and Pedagogy of Reading”, marked a crucial shift in the field, arguing that reading was not merely a mechanical skill but a complex social activity shaped by readers’ experiences. Huey emphasized the importance of “apperceptive filling in,” where readers constantly make inferences based on clues from the text, highlighting the active and constructive nature of reading comprehension. Huey remained influential and my own introduction to reading as a fascinating area of study included my reading of an updated edition of Huey’s book in the 1960s. The word recognition position became integrated with the use of context to form one of the two alternative positions proposing how kids should be taught to read.

Johns dedicates considerable attention to the “reading wars,” the ongoing debates between proponents of phonics-based instruction and those favoring whole-language approaches. He argues that these debates, often framed as a simplistic this or that options, fail to capture the complexity of reading acquisition and the nuances of effective teaching methods. However, as one might recognize from recent media accounts of mandated methods in different states, the methods to be used and the commercial materials to be purchased with state money are often described to parents and the general public in similar simplistic ways.

The book examines key figures and events in the reading wars, including Rudolf Flesch’s scathing critique of whole-language instruction in his 1955 bestseller, “Why Johnny Can’t Read”. Flesch’s book ignited a public debate, pushing back against the prevailing emphasis on whole-word recognition and advocating for a return to phonics-based instruction.

Johns also discusses the work of Jeanne Chall, whose research, culminating in her 1967 book “Learning to Read: The Great Debate,” offered a more complex perspective on the reading wars. Chall argued that a balanced approach incorporating both phonics and whole-language strategies was crucial, particularly in the early stages of reading development. I was pleased to see that my friend Dick Anderson who once headed the Center for the Study of Reading at the University of Illinois also received some space in Jones’ book as a supporter of a similar balanced approach.

The latter part of the book explores the impact of technology on reading, examining the development of teaching machines, programmed learning, and the rise of computers. Johns discusses the work of visionaries like Alan Kay, whose Dynabook project, though never fully realized, envisioned a portable computer designed to replace school textbooks and transform the learning process. Today’s iPad could represent the type of device Kay could only imagine.

Johns concludes by reflecting on the enduring challenges of reading in the digital age, posing questions about the differences between reading on paper and screens, and the implications of new technologies for literacy and learning.

While providing a thorough historical overview, Johns occasionally delves into intricate details of specific experiments or research methodologies, which may not be of interest to all readers. I find the description of actual studies of great interest and the answer to the question of how researchers study something as invisible as the processes of a mental skill such as reading and come up with explanations of what exactly is going on.

Reader, come home: The reading brain in a digital world

Maryanne Wolf’s *Reader, Come Home* presents a critical examination of how the digital age is reshaping the human brain’s ability to read deeply. She reviews the brain science of her previous book (Proust and the Squid), but then spends time on whether new technologies presenting text and multimedia alter how the brain adapts to the processing of text. There is more brain science in her first book for those wanting that focus and more focus on screen time, changes in attention span, and reading from a screen versus from paper in the book I am reviewing here.

The central argument of *Reader, Come Home* is that the human brain was not initially designed for reading; instead, reading rewired our brains in ways that changed our thinking. Wolf is deeply concerned that excessive exposure to screen-based media is now rewiring our brains in a different, less beneficial way. The skimming style of reading encouraged by digital platforms, where information is processed quickly and often superficially, is contrasted with the deeper, more reflective reading associated with print books. Wolf stresses that while the brain is highly plastic and can adapt, the quality of that adaptation depends on the stimuli it is exposed to regularly.

Wolf does not argue for a wholesale rejection of digital reading. Instead, she advocates for a balance, calling for the development of what she terms “biliterate” brains. These are brains that are adept at both skimming digital media and engaging in deep, reflective reading. Her emphasis is particularly on children, who, she argues, are especially vulnerable to the negative impacts of digital reading due to the greater plasticity of their brains. If children are exposed only to skimming on digital platforms, they may miss out on the profound cognitive and linguistic benefits that come from deep reading.

The book also provides practical advice for parents and educators. One of Wolf’s key suggestions is to encourage parents to read to their children from printed books rather than relying on digital devices that often come with built-in distractions. The concern is not just about reading comprehension, but also about how children learn to engage with and reflect on complex information, skills that are crucial for higher-order thinking.

A recurring theme in Reader, Come Home is that we are becoming passive consumers of information rather than active, critical thinkers. Wolf’s fear is that if we continue down this path, future generations will lose the ability to think deeply and critically. She draws on cognitive science to show how the brain’s attentional systems are being rewired in ways that diminish our capacity for sustained attention, a vital component of deep reading.

For those who enjoy scientific debates, contrast Wolf and Willingham’s perspective on this issue. Willingham explains the resistance to reading long-form content more as a decreased tolerance for boredom rather than the brain being shaped biologically.

The Reading Mind: A Cognitive Approach to Understanding How the Mind Reads

The Reading Mind is a comprehensive exploration of the mechanics of reading, offering both a cognitive and a practical perspective on how our brains process text. Willingham draws from a wealth of psychological research to explain the nuances of reading, from identifying phonemes to building meaning from full texts.

At its core, The Reading Mind breaks down reading into stages, beginning with letter and sound recognition and culminating in full comprehension of texts. Willingham explains that the ability to match letters to phonemes (basic units of sound) is crucial to reading development, particularly for children. As readers become more proficient, their ability to decode words becomes more automatic, freeing cognitive resources for understanding the meaning of sentences and paragraphs. In other works, the sound of words is initially quite important, but gives way to more automatic recognition of words. This cognitive model serves as a foundation throughout the book as Willingham discusses the importance of both bottom-up processes, like letter recognition, and top-down processes, such as using background knowledge to comprehend texts. I read somewhere that this simultaneous bottom-up and top-down processing can be described as interactive, compensatory processing. This means that multiple processes are going on simultaneously and they work both to support each other. Letter recognition is information by word recognition (the word provides a context that speeds up letter recognition). Words are more quickly recognized and their meaning is more effectively retrieved within meaningful sentences (sentences provide a context that informs word recognition and understanding). Understanding what we read is assisted by what we already know in general and what we know more specifically about the topic we are reading about (again a context effect improving more basic processes).

One of the more powerful demonstrations I know of considers the relative contribution of reading proficiency and subject knowledge to comprehension. Willingham provides an example based on soccer knowledge. The research study I was familiar with used baseball knowledge. Anyway, young readers were classified as more and less proficient readers and more and less knowledgeable of baseball. This gives you four groups – high skill, high knowledge; high skill, low knowledge; low skill, high knowledge; and low skill, low knowledge. All readers were asked to read a description of half an inning of a baseball game and later write what they remembered. This method allows the impact of reading skill to be teased apart from the impact of subject knowledge. The findings demonstrate that existing knowledge had a larger impact on recall than reading skill.

One of the book’s strengths is its emphasis on the role of motivation in reading. Willingham makes the case that motivation is as critical as cognitive skills when it comes to becoming a proficient reader. Readers who enjoy reading tend to read more, which in turn improves their reading abilities, creating a virtuous cycle. This insight is particularly valuable for educators and parents trying to encourage reluctant readers. Willingham argues that ease of access makes a big difference

A notable section of The Reading Mind addresses the potential impact of technology on reading habits. Willingham acknowledges the concern that digital distractions, such as social media and video games, might reduce the amount of time young people spend reading. However, he points out that these activities have not necessarily displaced reading time for most youth. Instead, he suggests that the issue lies in a reduced tolerance for boredom, which could make sustained reading more difficult for some. While Willingham does recommend limiting screen time, he is skeptical of alarmist claims that technology is fundamentally altering how children’s brains process information. His balanced view on this topic is refreshing in an age of widespread concern about the effects of digital media on cognitive development.

Conclusion:

My efforts here were to give enough of the flavor of each of these books to perhaps convince you to take a look. As I tried to suggest in the beginning of this post, all books are very approachable and take you in multiple directions addressing several topics that seem of current interest.

ChatLLM from Abacus AI

I have this issue with AI services. I have identified several services that provide me useful services (image generation for posts, edits for what I write, identification of journal articles relevant to my writing, and chats with my large collection of notes and highlights) The issue is no individual tool does a great job of all of these things and I don’t use any of the several individual tools enough to justify the $20 a month that seems to be the going rate for any given tool. I could keep telling myself that this retirement writing gig should be treated as a hobby that I can afford, but there is a principle involved here. I think of many of my posts as exploring tools for teachers and $75-100 a month in their situation is likely a bit much.

I have found a general-purpose AI service, the ChatLLM tool from Abacus AI, that I have for me what is unlimited use for $10 a month. For a month or so now, I have been duplicating my use of ChatLLM and ChatGPT and can find very little difference in what the tools generate. Abacus.AI has an introductory offer that is a little confusing. The first month is free, but you must purchase one month and then you can cancel after the first two months.

The interface is very similar to what you experience with other AI services. There is a prompt field and responses appear above. ChatLLM allows the individual series of chat interactions with a given purpose allowing you to return if you have a reason to pick up again on an earlier exploration.

ChatLLM appears to function as an API allowing you to select from different AI services. This option seems useful for those of us who like to explore the possible differences among the AI services that are available.

AbacusAI offers many features I have not bothered to explain here in detail. I have learned what I thought necessary to meet my personal needs and it should be very easy for anyone with any experience with other platforms to get started. Here is a more complete review by another writer.

How many AI tools?

It’s not that I don’t find AI to be useful. I generate a half dozen images a month to embellish my writing. I search for journal articles I then read to examine an educational issue I want to write about. I examine what I have written to identify errors in grammar or syntax or even identify my use of passive voice which I still can’t figure out. My issue is the monthly subscription fees for the multiple tools that best suit these and other uses. It is simply difficult to justify the $20 a month fee which seems to be the going rate for each of the services and the level of use I make of each service.

I regard my use of AI as both a benefit to personal productivity, but also a subject matter I explore and write about. Writing about the intersection of technology and education is a retirement hobby and I don’t need to do what I do on a budget. However, I don’t think this is true for everyone and I can set as a personal goal an exploration of the financial issues others might need to consider. AI tools differ in how flexible they are. Often, the less flexible tools are optimized to accomplish a specific set of tasks and this narrow range increases ease of use. Users can find themselves evaluating the cost-effectiveness of options based on ease of use versus total cost.

Grammarly as an example

As someone who spends a great deal of time writing, it is worth my time to consider how AI tools can be used to improve the productivity of the time I spend writing and the quality of what I write. Grammarly is a tool suited to such goals. I have relied on both the free and pro versions of Grammarly for a quick way to edit my writing. This is a great product I find helpful. Again, the issue is the Pro version adds another $12 to the total of my monthly subscriptions bill. The free version is great for basic errors, but the pro version is necessary for complete sentence rewrites. It is helpful to compare what I said with the suggested rewrite to decide whether I want to accept the alternate version.

What I have been exploring lately is the use of more general-purpose AI tools (e.g., ChatGPT, Abacas.ai) as an alternative. I understood that many others were using such tools in this matter, but because I had already been using Grammarly I had not invested the time to explore how more flexible tools might be used to achieve similar goals. Here is the approach I have settled on. I use a multi-level prompt to specify what I want to learn from an evaluation of something I have written. I keep this prompt in a note app so that I can copy and paste the prompt at the beginning of the content I want to evaluate. The prompt appears below. The prompt is written to be flexible so that I can adapt it to different circumstances by adding or removing specific guidelines. For example, I realize I often write in passive voice and some tasks should not include text expressed in this way. The guideline “write in active voice” can be included when I think this approach is important. If writing for a specific age group might be a goal, a guideline related to this goal can be inserted.

To demonstrate what this prompt accomplishes, I will take what I written here to this point and apply the prompt.

Evaluate the following content using the following guidelines:

Correct spelling errors
Correct grammatical errors
Correct punctuation errors
Write in active voice
Suggest corrections
Only list the lines containing errors and the proposed corrections
Add an explanation for the need for a correction

[Insert content to be evaluated here]

Response from Abacas.ai.

1. **Original:** I examine what I have written to identify errors in grammar or syntax or even identify my use of passive voice which I still can’t figure out.

   **Correction:** I examine what I have written to identify errors in grammar or syntax and even identify my use of passive voice, which I still can’t figure out.

   **Explanation:** Added a comma before “which” to correctly punctuate the non-restrictive clause.

2. **Original:** It is simply difficult to justify the $20 a month fee which seems to be the going rate for each of the services and the level of use I make of each service.

   **Correction:** It is simply difficult to justify the $20-a-month fee, which seems to be the going rate for each of the services and the level of use I make of each service.

   **Explanation:** Added a hyphen in “$20-a-month” to correctly form a compound adjective and a comma before “which” to punctuate the non-restrictive clause.

3. **Original:** I regard my use of AI as both a benefit to personal productivity, but also a subject matter I explore and write about.

   **Correction:** I regard my use of AI as both a benefit to personal productivity and a subject matter I explore and write about.

   **Explanation:** Replaced “but also” with “and” to correct the parallel structure.

4. **Original:** Writing about the intersection of technology and education is a retirement hobby and I don’t need to do what I do on a budget.

   **Correction:** Writing about the intersection of technology and education is a retirement hobby, and I don’t need to do what I do on a budget.

   **Explanation:** Added a comma before “and” to separate two independent clauses.

5. **Original:** Grammarly as an example

   **Correction:** Grammarly is an example.

   **Explanation:** Added “is” to form a complete sentence.

6. **Original:** Again, the issue is the Pro version adds another $12 to the total of my monthly subscriptions bill.

   **Correction:** Again, the issue is that the Pro version adds another $12 to the total of my monthly subscription bill.

   **Explanation:** Added “that” for clarity and changed “subscriptions” to “subscription” for correct singular form.

7. **Original:** What I have been exploring lately is the use of more general-purpose AI tools (e.g., ChatGPT, Abacas.ai) as an alternative.

   **Correction:** What I have been exploring lately is the use of more general-purpose AI tools (e.g., ChatGPT, Abacus.ai) as an alternative.

   **Explanation:** Corrected the spelling of “Abacas.ai” to “Abacus.ai.”

8. **Original:** I understood that many others were using such tools in this matter, but because I had already been using Grammarly I had not invested the time to explore how more flexible tools might be used to achieve similar goals.

   **Correction:** I understood that many others were using such tools in this manner, but because I had already been using Grammarly, I had not invested the time to explore how more flexible tools might be used to achieve similar goals.

   **Explanation:** Changed “matter” to “manner” for correct word usage and added a comma after “Grammarly” to separate clauses.

The feedback I have received would normally have resulted in my making several adjustments. I have not done so for you to consider both the original and the suggestions. The feedback makes specific suggestions and I either copy and paste the suggestions to the original source material or simply retype what needs to be fixed. This is clumsier than just clicking on the recommendation offered by Grammarly and it often requires that I use the search function in a longer text to locate the offending sentence. When writing on my desktop machine I simply open a second window and move between one window with the AI feedback and the original document to make adjustments.